Automatic age recognition, call-type classification, and speaker identification of Zebra Finches (Taeniopygia guttata) using hidden Markov models (HMMs)

International Journal of Speech Technology - Tập 26 - Trang 641-650 - 2023
Marek B. Trawicki1
1Marquette University, Milwaukee, USA

Tóm tắt

Hidden Markov models (HMMs) were developed and implemented to discriminate between each of the 2 ages, 11 call-types, and 51 speakers of birds using cross-validation on the recordings in the 3314 database for chick (19–25 days of age) and adult (60 days–7 years of age) vocalizations of Zebra Finches (Taeniopygia guttata). By applying both temporal [delta (velocity) and delta-delta (acceleration) coefficients] and spectral [Mel-Frequency Cepstral Coefficients (MFCCs)] features, the HMMs produced excellent performance with accuracies on the three tasks: (1) 96.68% (age recognition); (2) 94.62% (chicks) and 79.30% (adults) (call-type classification); and (3) 55.32% (12 speakers, chicks) and 16.78% (33 speakers, adults) to 100.00% (2 speakers, chicks), and 100.00% (3 speakers adults) (speaker identification). Based on the performances, the HMMs could be extended to other animals for automatic recognition, classification, and identification tasks.

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International Journal of Speech Technology

Tập 26

641-650

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